Senior Site Reliability Engineer

Posted 3 Days Ago
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Īnd, Chamba, Himāchal Pradesh
Senior level
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
The Senior Site Reliability Engineer will be responsible for creating and managing resilient deployment pipelines, automating infrastructure management, and troubleshooting issues. They will ensure high availability of large scale services and collaborate with engineering teams to optimize infrastructure performance. The role requires a strong background in DevOps and proficiency in various automation tools and scripting languages.
Summary Generated by Built In

NVIDIA’s Infrastructure, Planning and Processes (IPP) organization is seeking a hard-working and experienced Site Reliability/DevOps Engineer, with strong background in Infrastructure Management, Monitoring, Automation, & System Administration, to join our GVS Operations Team in Pune. The IPP Org provides Infrastructure, Products & Services for multiple software teams including GPU, Mobile, and Automotive divisions working on Nvidia's extraordinary products & services.

 

The team is responsible for hosting, enabling & running the large scale private cloud systems & services, for our in-house Build & Test framework. The cloud hosts a heterogeneous mix of machines and devices with various operating systems (Windows/Linux/Android, etc.), running with NVIDIA GPUs and Tegra Processors.

 

What you’ll be doing:

  • Create resilient, scalable, and efficient Build and deployment pipelines.

  • Design and implement complex automation platforms to identify & resolve operational inefficiencies.

  • Triaging software, hardware and infrastructure issues and maintaining high availability for our infrastructure & services.

  • Deploying & Monitoring critical high performance, large scale services running on Geo-distributed systems.

  • Continuously Strive for efficient utilization & management of the infrastructure.

  • Automate processes for enabling developers to adopt self-service practices, while ensuring compliance with security standards.

  • Work with architects and engineers across the teams to review the designs & solutions during development and deployment phases.

  • Collaborate with our other engineering teams to deliver reliable, robust, and high-performance capability of the underlying infra.

  • Mine & analyse data from multiple sources for identifying scaling & optimization opportunities.

 

What we need to see:

  • Bachelor’s or Master’s degree in computer science, Software Engineering, or equivalent experience with 8+ years of experience in a DevOps environment.

  • Strong hands-on experience in Configuring, maintaining, and building upon deployments of industry-standard tools (e.g. Kubernetes, Jenkins, Docker, CMake, Gitlab, Jira, etc)

  • Working Experience in monitoring & maintaining large-scale infrastructure applications running in a microservice-based architecture.

  • Proficient with Virtualization architecture with strong experience in Kubernetes, VMs, & Dockers.

  • Experience with CI/CD systems such as GitLab, GitOps, Jenkins, Terraform, etc.

  • Experienced in data pipelines setup via Kafka, Filebeat and visualization using tools like Elastic search, Grafana, Kibana, Tableau

  • Strong Python scripting skills, with proven background of using/writing JSON/REST APIs.

  • Fluency in using MySQL or equivalent NoSQL databases queries

  • Solid understanding of configuration management tools like, Chef, Puppet, Ansible, etc.

  • Working Experience with Perforce, GIT or any other version control system.

  • Experience with telemetry and alerting systems such as Kibana, Elastic Search, Zabbix, Grafana, and Prometheus to create rich visualizations of system health over time.

  • Ability to self-manage, show leadership, mentor others and communicate well.

 

Ways to stand out from the crowd:

  • Understanding of networking concepts like TCP/IP and firewall management.

  • Exposure to web apps/dashboards on frameworks like Django, AngularJS, VueJS, etc.

  • High level understanding of Build and Test systems.

  • Experience in Building regression detection systems by analyzing real-time production data, emphasizing important metrics.

  • Innovating with industry-standard tools and collaborating with the open source community

Top Skills

Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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